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-rw-r--r--3rdparty/pybind11/tests/test_numpy_vectorize.py168
1 files changed, 119 insertions, 49 deletions
diff --git a/3rdparty/pybind11/tests/test_numpy_vectorize.py b/3rdparty/pybind11/tests/test_numpy_vectorize.py
index 0e9c8839..4e6b2d19 100644
--- a/3rdparty/pybind11/tests/test_numpy_vectorize.py
+++ b/3rdparty/pybind11/tests/test_numpy_vectorize.py
@@ -1,10 +1,8 @@
+# -*- coding: utf-8 -*-
import pytest
from pybind11_tests import numpy_vectorize as m
-pytestmark = pytest.requires_numpy
-
-with pytest.suppress(ImportError):
- import numpy as np
+np = pytest.importorskip("numpy")
def test_vectorize(capture):
@@ -19,28 +17,40 @@ def test_vectorize(capture):
assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
with capture:
assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36])
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=3)
my_func(x:int=3, y:float=4, z:float=3)
"""
+ )
with capture:
- a = np.array([[1, 2], [3, 4]], order='F')
- b = np.array([[10, 20], [30, 40]], order='F')
+ a = np.array([[1, 2], [3, 4]], order="F")
+ b = np.array([[10, 20], [30, 40]], order="F")
c = 3
result = f(a, b, c)
assert np.allclose(result, a * b * c)
assert result.flags.f_contiguous
# All inputs are F order and full or singletons, so we the result is in col-major order:
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=10, z:float=3)
my_func(x:int=3, y:float=30, z:float=3)
my_func(x:int=2, y:float=20, z:float=3)
my_func(x:int=4, y:float=40, z:float=3)
"""
+ )
with capture:
- a, b, c = np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
+ a, b, c = (
+ np.array([[1, 3, 5], [7, 9, 11]]),
+ np.array([[2, 4, 6], [8, 10, 12]]),
+ 3,
+ )
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=3)
my_func(x:int=3, y:float=4, z:float=3)
my_func(x:int=5, y:float=6, z:float=3)
@@ -48,10 +58,13 @@ def test_vectorize(capture):
my_func(x:int=9, y:float=10, z:float=3)
my_func(x:int=11, y:float=12, z:float=3)
"""
+ )
with capture:
a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=2)
my_func(x:int=2, y:float=3, z:float=2)
my_func(x:int=3, y:float=4, z:float=2)
@@ -59,10 +72,13 @@ def test_vectorize(capture):
my_func(x:int=5, y:float=3, z:float=2)
my_func(x:int=6, y:float=4, z:float=2)
"""
+ )
with capture:
a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=2)
my_func(x:int=2, y:float=2, z:float=2)
my_func(x:int=3, y:float=2, z:float=2)
@@ -70,10 +86,17 @@ def test_vectorize(capture):
my_func(x:int=5, y:float=3, z:float=2)
my_func(x:int=6, y:float=3, z:float=2)
"""
+ )
with capture:
- a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F'), np.array([[2], [3]]), 2
+ a, b, c = (
+ np.array([[1, 2, 3], [4, 5, 6]], order="F"),
+ np.array([[2], [3]]),
+ 2,
+ )
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=2)
my_func(x:int=2, y:float=2, z:float=2)
my_func(x:int=3, y:float=2, z:float=2)
@@ -81,36 +104,53 @@ def test_vectorize(capture):
my_func(x:int=5, y:float=3, z:float=2)
my_func(x:int=6, y:float=3, z:float=2)
"""
+ )
with capture:
a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=2)
my_func(x:int=3, y:float=2, z:float=2)
my_func(x:int=4, y:float=3, z:float=2)
my_func(x:int=6, y:float=3, z:float=2)
"""
+ )
with capture:
- a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F')[::, ::2], np.array([[2], [3]]), 2
+ a, b, c = (
+ np.array([[1, 2, 3], [4, 5, 6]], order="F")[::, ::2],
+ np.array([[2], [3]]),
+ 2,
+ )
assert np.allclose(f(a, b, c), a * b * c)
- assert capture == """
+ assert (
+ capture
+ == """
my_func(x:int=1, y:float=2, z:float=2)
my_func(x:int=3, y:float=2, z:float=2)
my_func(x:int=4, y:float=3, z:float=2)
my_func(x:int=6, y:float=3, z:float=2)
"""
+ )
def test_type_selection():
assert m.selective_func(np.array([1], dtype=np.int32)) == "Int branch taken."
assert m.selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken."
- assert m.selective_func(np.array([1.0j], dtype=np.complex64)) == "Complex float branch taken."
+ assert (
+ m.selective_func(np.array([1.0j], dtype=np.complex64))
+ == "Complex float branch taken."
+ )
def test_docs(doc):
- assert doc(m.vectorized_func) == """
- vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object
+ assert (
+ doc(m.vectorized_func)
+ == """
+ vectorized_func(arg0: numpy.ndarray[numpy.int32], arg1: numpy.ndarray[numpy.float32], arg2: numpy.ndarray[numpy.float64]) -> object
""" # noqa: E501 line too long
+ )
def test_trivial_broadcasting():
@@ -118,16 +158,24 @@ def test_trivial_broadcasting():
assert vectorized_is_trivial(1, 2, 3) == trivial.c_trivial
assert vectorized_is_trivial(np.array(1), np.array(2), 3) == trivial.c_trivial
- assert vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3) == trivial.c_trivial
+ assert (
+ vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3)
+ == trivial.c_trivial
+ )
assert trivial.c_trivial == vectorized_is_trivial(
- np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3)
- assert vectorized_is_trivial(
- np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2) == trivial.non_trivial
- assert vectorized_is_trivial(
- np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2) == trivial.non_trivial
- z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype='int32')
- z2 = np.array(z1, dtype='float32')
- z3 = np.array(z1, dtype='float64')
+ np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
+ )
+ assert (
+ vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2)
+ == trivial.non_trivial
+ )
+ assert (
+ vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2)
+ == trivial.non_trivial
+ )
+ z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype="int32")
+ z2 = np.array(z1, dtype="float32")
+ z3 = np.array(z1, dtype="float64")
assert vectorized_is_trivial(z1, z2, z3) == trivial.c_trivial
assert vectorized_is_trivial(1, z2, z3) == trivial.c_trivial
assert vectorized_is_trivial(z1, 1, z3) == trivial.c_trivial
@@ -137,7 +185,7 @@ def test_trivial_broadcasting():
assert vectorized_is_trivial(1, 1, z3[::2, ::2]) == trivial.non_trivial
assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4]) == trivial.c_trivial
- y1 = np.array(z1, order='F')
+ y1 = np.array(z1, order="F")
y2 = np.array(y1)
y3 = np.array(y1)
assert vectorized_is_trivial(y1, y2, y3) == trivial.f_trivial
@@ -158,30 +206,41 @@ def test_trivial_broadcasting():
def test_passthrough_arguments(doc):
assert doc(m.vec_passthrough) == (
- "vec_passthrough(" + ", ".join([
- "arg0: float",
- "arg1: numpy.ndarray[float64]",
- "arg2: numpy.ndarray[float64]",
- "arg3: numpy.ndarray[int32]",
- "arg4: int",
- "arg5: m.numpy_vectorize.NonPODClass",
- "arg6: numpy.ndarray[float64]"]) + ") -> object")
-
- b = np.array([[10, 20, 30]], dtype='float64')
+ "vec_passthrough("
+ + ", ".join(
+ [
+ "arg0: float",
+ "arg1: numpy.ndarray[numpy.float64]",
+ "arg2: numpy.ndarray[numpy.float64]",
+ "arg3: numpy.ndarray[numpy.int32]",
+ "arg4: int",
+ "arg5: m.numpy_vectorize.NonPODClass",
+ "arg6: numpy.ndarray[numpy.float64]",
+ ]
+ )
+ + ") -> object"
+ )
+
+ b = np.array([[10, 20, 30]], dtype="float64")
c = np.array([100, 200]) # NOT a vectorized argument
- d = np.array([[1000], [2000], [3000]], dtype='int')
- g = np.array([[1000000, 2000000, 3000000]], dtype='int') # requires casting
+ d = np.array([[1000], [2000], [3000]], dtype="int")
+ g = np.array([[1000000, 2000000, 3000000]], dtype="int") # requires casting
assert np.all(
- m.vec_passthrough(1, b, c, d, 10000, m.NonPODClass(100000), g) ==
- np.array([[1111111, 2111121, 3111131],
- [1112111, 2112121, 3112131],
- [1113111, 2113121, 3113131]]))
+ m.vec_passthrough(1, b, c, d, 10000, m.NonPODClass(100000), g)
+ == np.array(
+ [
+ [1111111, 2111121, 3111131],
+ [1112111, 2112121, 3112131],
+ [1113111, 2113121, 3113131],
+ ]
+ )
+ )
def test_method_vectorization():
o = m.VectorizeTestClass(3)
- x = np.array([1, 2], dtype='int')
- y = np.array([[10], [20]], dtype='float32')
+ x = np.array([1, 2], dtype="int")
+ y = np.array([[10], [20]], dtype="float32")
assert np.all(o.method(x, y) == [[14, 15], [24, 25]])
@@ -190,7 +249,18 @@ def test_array_collapse():
assert not isinstance(m.vectorized_func(np.array(1), 2, 3), np.ndarray)
z = m.vectorized_func([1], 2, 3)
assert isinstance(z, np.ndarray)
- assert z.shape == (1, )
+ assert z.shape == (1,)
z = m.vectorized_func(1, [[[2]]], 3)
assert isinstance(z, np.ndarray)
assert z.shape == (1, 1, 1)
+
+
+def test_vectorized_noreturn():
+ x = m.NonPODClass(0)
+ assert x.value == 0
+ m.add_to(x, [1, 2, 3, 4])
+ assert x.value == 10
+ m.add_to(x, 1)
+ assert x.value == 11
+ m.add_to(x, [[1, 1], [2, 3]])
+ assert x.value == 18
generated by cgit v1.2.3 (git 2.25.1) at 2024-07-04 23:36:32 +0000